1. Field of the Invention
The present invention relates to an image processing apparatus configured to detect an object from an image and a method thereof.
2. Description of the Related Art
Image processing methods for automatically detecting a certain object pattern from an image is very useful, for example, in determining a human face. Such image processing methods can be used for various applications including communication conference, man-machine interface, security, monitor/system for tracing a human face, and image compression. A technique for detecting an object from an image is discussed in “Rapid Object Detection using Boosted Cascade of Simple Features” of Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR '01).
The above-described document discusses improvement of discrimination accuracy by effectively combining many weak discriminators using AdaBoost. Further, the weak discriminators are connected in series so as to form a cascade detector. Each of the weak discriminators uses a Haar-type rectangle feature quantity in the discrimination. By using an integrated image, each of the weak discriminators can calculate the rectangle feature quantity at a high speed.
The cascade detector removes a pattern that is apparently not an object by using a simple discriminator (i.e., discriminator for a small amount of calculation) arranged at an early stage of the detection. After then, the cascade detector determines whether the remaining patterns are objects by using a discriminator having higher identification capability (i.e., discriminator capable of a large amount of complex calculations) arranged at a subsequent stage. In this way, since the need for performing complex determination on all candidates is unnecessary, the determination can be performed at a high speed.
Generally, in searching an object which is included in an image taken by a digital camera, a field is scanned with a sub-window (frame) of a certain size, and then two-class discrimination is performed. According to the two-class discrimination, whether a pattern image (i.e., image in the sub-window) is an object is determined. Thus, removing a pattern that is not an object at an early stage is a key to realizing reduced detection time.
In order to speedily narrow down a pattern that may be an object at an early stage, a conventional weak discriminator thoroughly searches a position or a size of a local region in which an amount of calculation that is necessary in narrowing down the pattern is minimum, and combines the obtained results.
However, reading speed and transmission speed of a pattern image or an integral image has been a bottleneck in increasing the processing speed.